International Conference on Agents and Artificial Intelligence
Authors
H. Greblă, C. Rusu, Adrian Sterca, Darius Bufnea, Virginia Niculescu
Abstract
The purpose of this work is to study the possible approaches to build a recommendation system that could help students in organizing their work and improving their results. More specifically, we intend to predict grades of a student for future exams, based on his/her previous results and the past grades received by all students from the same series/group. We have tried several machine learning methods for predicting future student grades, and finally we obtained good results, namely a mean absolute prediction error smaller than 1. The best variant proved to be the one based on neural networks that leads to a mean absolute prediction error smaller than 0.5. These results show the practical applicability of our proposed methodology, and consequently, we built, based on these, a practical recommendation system available to students as a web application.
Citation
@Inproceedings{Greblă2022RecommendationSF,
author = {H. Greblă and C. Rusu and Adrian Sterca and Darius Bufnea and Virginia Niculescu},
booktitle = {International Conference on Agents and Artificial Intelligence},
title = {Recommendation System for Student Academic Progress},
year = {2022}
}